Search results

Following Philip Selznick’s lead in using pragmatist social science to understand issues of public concern we conducted a study of failed innovation in the commercial construction industry (CCI). We find that social heuristics – collectively constructed and maintained interpretive decision-making frames – significantly shape economic and non-economic decision-making practices. Social heuristics are the outcome of industry-based “institutionalization processes” and are widely held and commonly relied on in CCI to reduce uncertainty endemic to decision-making; they provide actors with both a priori and ex post facto justifications for economic decisions that appear socially rational to industry co-participants. In the CCI – a project-centered production network – social heuristics as shared institutions sustain network-based social order but in so doing discourage novel technologies and impede innovation. Social heuristics are actor-level constructs that reflect macro-level institutional arrangements and networked production relations. The concept of social heuristics offers the promise of developing a genuinely social theory of individual economic choice and action that is historically informed, contextually situated, and neither psychologically nor structurally reductionist.

When entrepreneurs create new ventures, they struggle with making consequential decisions under severe restrictions such as tight deadlines, limited resources, and lack of information. Making challenging decisions inherently requires creativity as entrepreneurs improvise and work around the limitations they face. Under these conditions, entrepreneurs resort to their heuristics and biases instead of rational decision models. Entrepreneurs employ – sometimes for better and sometimes for worse – a myriad of rule-setting heuristics and experience-based biases to navigate the difficult path between novelty and utility. In this chapter, the authors answer Shepherd, Williams, and Patzelt’s (2015) call for research into how entrepreneurs leverage heuristics and biases in decision-making and the benefits they gain as a result. The authors explore how entrepreneurs introduce heuristics and biases at different stages of their decision-making process using a qualitative study of 21 new ventures. The results attest to entrepreneurs’ ingenuity and creativity in managing complexity, ambiguity, and uncertainty.

While recent research has referred to a cognitive view on “business modelling,” it remains unclear in specifying the cognitive foundations of how such modelling happens. This paper proposes building on heuristics as models of individual cognition, which have proved effective foundations of adaptive individual and managerial behaviors. By also drawing on gestalt theory to specify principles of modelling as rule-based form giving, we propose business modelling as a managerial cognitive process of configuring heuristics. The paper makes three contributions. First, we introduce heuristics to the business modelling literature and so provide an established theory of adaptive individual behavior that strengthens the cognitive foundations of business modelling. Second, we conceptualize and theorize on the cognitive activity of business modelling as an iterative process of configuring heuristics by applying gestalt principles. Although the literature on business models has referred to the theories of configurations and gestalt, it has been left to this work to make the theoretical linkages between heuristics, gestalt theory and business modelling explicit. Third, our work contributes to the micro-foundations of the cognitive processes underlying business modelling and thus to broader accounts of adaptive managerial behaviors.

The way organizations cope with uncertainty in strategic decision making is prominently discussed. Concepts such as heuristics and simple rules are gaining increasing attention in strategic management research. However, despite their importance, little is known how heuristics and simple rules operate. Our qualitative study reveals that, first, strategic decisions consist of three basic elements: single rules, rule patterns, and emotional handling. Second, we find that firms develop generalizable rule patterns which follow a sequential order of inter-linked rules. Based on the findings we introduce the concept of organizational heuristics as inter-linked rule patterns drawing on organizational experience.

Our editorial argues that categories theory can be advanced by embracing heuristics research, and the insight that audiences often evaluate items based on multiple valued criteria. Thus, rather than building on extant theory – which suggests that categories embody specific evaluative criteria, or that audiences operate according to a set “theory of value” – the authors argue that hybrids research would benefit from attending to the underlying processes that actors use to weigh and balance the diverse considerations that guide their decisions. The authors define and discuss three commonly used heuristics (satisficing, lexicographic preferences, and elimination by aspects), and show how these might lead audiences to support different types of hybrid entities.

Herbert A. Simon and Alan Newell won the Turing Award jointly in Computer Science for foundational work on Artificial Intelligence. Simon also won the Nobel Prize in Economics for the concept of “bounded rationality.” In both cases, the same heuristic was deemed fundamental: “Search till a satisfactory solution is found.” We argue that behavioral strategy can learn a great deal from the Theory of Computational Complexity and Artificial Intelligence. These fields can provide a sounder theoretical grounding for bounded rationality and for the necessity and usefulness of heuristics. Finally, a concept of “organizational intractability” based roughly on the metaphor provided by the Theory of Computational Complexity may be useful in determining what analytical decision technologies are actually intractable in real organizations with constraints on time and managerial attention.

Increasing evidence suggests that choice behaviour in real world may be guided by principles of bounded rationality as opposed to typically assumed fully rational behaviour, based on the principle of utility-maximization. Under such circumstances, conventional rational choice models cannot capture the decision processes. The purpose of the chapter is to propose a modeling framework that can capture both decision outcome and decision process.

The modeling framework incorporates a discrete cognitive representation structure and implies several decision heuristics, such as conjunctive, disjunctive and lexicographic rules. This allows modeling unobserved decision heterogeneity involved in a single decision, for example, in the form of a latent-class specification, taking into account mental effort, risk perception and expected outcome as explanatory factors.

Two models based on this framework are applied to decision problems underlying pedestrian shopping behaviour and compared with conventional multinomial logit models. The results show that the proposed models may not be superior to logit models in terms of model selection criteria due to the extra complexity in selecting heuristics, but suggest more interesting insights to the underlying decision mechanisms.

Understanding decision processes additional to outcomes is a promising research direction. A more developed model should take into account more contextual and socio-demographic factors in the heuristic selection part. The assumptions of information processing must be subject to empirical tests to validate the model.

The proposed modeling framework bridges the long-existing contradicting approaches in the field of decision modeling, namely the rational approach and the bounded rational approach, by proving that non-compensatory decision heuristics can be inferred from compensatory model formulations with discretized information representations and decision criteria assumed. It also incorporates a heuristic choice part into the decision processes in the form of latent-class specifications and shows the viability of the new modeling framework.

This chapter aims to identify the impact of misbelief and heuristics on the engagement of giggers and customers with gigging organisations. This is of value due to the plethora of gigging opportunities and our lack of knowledge about how and why people choose to take up these opportunities. In addition, the gigs may frequently go unrecorded with payments made through systems such as PayPal which can allow international payments to be made without remittances. This chapter utilises some of the primary evolutionary theories to explore the efficacy and conflict in communications between gigging organisations, their customers and providers (giggers). Those selected are: misbelief in the conscious mind; and heuristics, such as the availability and confirmatory heuristics in the unconscious mind. Misbelief is addressed as a spandrel, and heuristics are discussed through the lens of fast and frugal approaches. Through a text analysis of 77 international gigging organisations, the messages conveyed are assessed against both evolutionary theory and prior research into the gig economy. The findings are that evolutionary psychology provides a useful framework for analysing these messages, as well as aiding understanding of gigging behaviours. HRM practitioners could make use of this form of analysis to support their design of interactions with giggers to ensure clarity on both sides.